포인트 클라우드 기반 선체 구조 변형 탐지 알고리즘 적용 연구

• Published in: 大韓造船學會 論文集 Vol. 59; no. 4; pp. 235 - 242
• Main Authors: 송상호, 이갑헌, 한기민, 장화섭, Song, Sang-ho, Lee, Gap-heon, Han, Ki-min, Jang, Hwa-sup
• Format: Journal Article
• Language: English; Korean
• Published: 대한조선학회 01.08.2022
• Subjects: 조선공학; 3
• ISSN: 1225-1143; 2287-7355
• DOI: 10.3744/SNAK.2022.59.4.235

As ship condition inspection technology has been developed, research on collecting, analyzing, and diagnosing condition information has become active. In ships, related research has been conducted, such as analyzing, detecting, and classifying major hull failures such as cracks and corrosion using 2D and 3D data information. However, for geometric deformation such as indents and bulges, 2D data has limitations in detection, so 3D data is needed to utilize spatial feature information. In this study, we aim to detect hull structural deformation positions. It builds a specimen based on actual hull structure deformation and acquires a point cloud from a model scanned with a 3D scanner. In the obtained point cloud, deformation(outliers) is found with a combination of RANSAC algorithms that find the best matching model in the Octree data structure and dataset.